
201 - 500 employees
Founded 1996
đŚ Logistics
âď¸ SaaS
đ¤ Artificial Intelligence
Logistics ⢠SaaS ⢠Artificial Intelligence
Intelligent Audit is a transportation cost-control and logistics software company that automates freight and parcel audit & recovery and provides logistics spend intelligence, real-time visibility, claims management, carrier payments, and contract management. The company offers AI-powered capabilities (Yosiâ˘, DeepDetectAIâ˘, Pollyâ˘) for continuous detection of errors, fraud, service misuse, and cost patterns, plus scenario modeling and network/parcel optimization tools. Intelligent Audit positions itself as a B2B provider for shippers and 3PLs and emphasizes a mix of technology, services, and operational expertise ("proven since 1996").
đ October 20
đď¸ New Jersey â Remote
đľ $70k - $90k / year
â° Full Time
đĄ Mid-level
đ Senior
đď¸ Platform Engineer
đť Ghost score 0%
Where this job comes from
Posted on Intelligent Audit's careers page, not through a job board
First seen by Remote Rocketship October 20
Still open on Intelligent Audit's site. Checked 4 hours ago.

201 - 500 employees
Founded 1996
đŚ Logistics
âď¸ SaaS
đ¤ Artificial Intelligence
Logistics ⢠SaaS ⢠Artificial Intelligence
Intelligent Audit is a transportation cost-control and logistics software company that automates freight and parcel audit & recovery and provides logistics spend intelligence, real-time visibility, claims management, carrier payments, and contract management. The company offers AI-powered capabilities (Yosiâ˘, DeepDetectAIâ˘, Pollyâ˘) for continuous detection of errors, fraud, service misuse, and cost patterns, plus scenario modeling and network/parcel optimization tools. Intelligent Audit positions itself as a B2B provider for shippers and 3PLs and emphasizes a mix of technology, services, and operational expertise ("proven since 1996").
⢠Build and improve AI agents and automations for Finance, Operations and Customer Support ⢠Prototype AI workflows, test results and use data to demonstrate time savings or improved outcomes ⢠Develop Python applications, APIs and scripts connecting AI tools to internal systems through APIs and MCP servers ⢠Help build and improve AI infrastructure with guidance from the team lead ⢠Test and review AI-generated code and model output while following security, privacy, access-control and data-handling practices ⢠Document workflows, prompts and operating procedures, and share examples for effective AI-tool use ⢠Build and manage multi-agent workflows and agent-assisted coding tasks; check results and escalate questions or risks ⢠Help deploy and run AI services using Docker, Linux and existing CI/CD pipelines ⢠Help set up monitoring and alerts, read logs, investigate failures and implement reviewed fixes ⢠Collaborate with colleagues to understand automation needs, communicate progress, manage competing tasks and improve solutions through feedback
⢠Working skills in Python and some shell scripting, demonstrated through coursework, internships or personal projects ⢠Hands-on experience using LLMs or AI APIs to build a tool, project or hackathon solution ⢠Understanding of basic software development practices, including testing, Git, documentation and code review ⢠Practical experience managing multi-agent workflows, including agent-assisted coding projects, with the ability to explain how results were checked ⢠Comfort using Linux, Git and the command line ⢠Exposure to Docker, cloud services such as AWS or DigitalOcean, or CI/CD through classes, internships or personal projects ⢠Curiosity about repetitive business tasks and willingness to learn how to turn them into reliable automations ⢠Habit of validating AI output and checking that a solution works before calling it complete ⢠Problem-solving skills, attention to detail and willingness to ask for help and learn from feedback ⢠Clear communication, collaboration and ability to manage multiple tasks with guidance on priorities ⢠Interest in learning AI tooling, deployment practices and reliable operation of production services ⢠Bachelor's degree in Computer Science, Software Engineering, Information Systems or a related field, recently earned or nearing completion ⢠A practical example of an AI or automation project built, tested and available for discussion, including what was learned and how the outcome was verified ⢠Willingness to build, deploy and support AI tools while learning directly from the team lead ⢠Preferred: SQL and basic database experience ⢠Preferred: Exposure to infrastructure-as-code tools such as Ansible ⢠Preferred: Familiarity with agent frameworks, prompt engineering or evaluating model output ⢠Preferred: Internship or project involving DevOps, SRE or platform engineering ⢠Preferred: Experience extending AI agents or automations beyond an initial prototype ⢠No minimum years of professional experience are required
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